adding quantitative measures to qualitative decision making
DESCRIPTION
Presented by: Morganna Keith and Mary StubbsTRANSCRIPT
Adding Quantitative Measures to Qualitative
Decision Making
• © Honeywell International
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Presenters
• Mary Stubbs
- Sr Project Engineer Manager, PMP, MBB
- Honeywell, Tempe, AZ
• Ganna Keith
- Product Design Engineer
- Honeywell, Torrance, CA
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Why Team Decision Making?
© Paragon Books, 2012
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Team Behaviors
• High performing team
- http://www.youtube.com/watch?v=C2YZnTL596Q
• Dysfunctional team
- http://www.youtube.com/watch?v=9yFkMQO0eyM
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• Time bound
Quality Team Decision Making
• Documented
• Full team engagement
• Structured
• Diversity of opinion / all stakeholders
• Fact based
• Clear problem statement
• Strong Facilitation
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• Honor the team’s commitment
- Start on time, end on time
- Thank the team for their participation
- Don’t feel that you have to use all of the time allotted
Facilitating Team Decision Making
• Know when the team needs a break
• Give directions clearly and briefly
• Set the stage by providing context
- Objectives, prior decisions, in/out of scope
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Facilitating Team Decision Making
• Deal head on with bad behaviors and encourage participation
- “Thank you for your insight, Linda, let’s hear from the rest of the team.”
- “Remember the 3-knock rule – One conversation at a time.”
- “What do you think, Natalie?”
• Help the team to communicate through echoing
- I believe I heard “…”, is that correct?
• Ask questions instead of making statements
- I wonder if we need to consider…
- What did we do the last time that we faced a similar situation? How did that work out?
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Facilitating Team Decision Making
• Keep the team on track, but allow for team process
- If the team is doing fine it is best to be quiet
- Some storming is expected and productive
- Know when to step in and “parking lot” an issue if the team is going down a “rat hole”
• Stay neutral, let the team make the decision
• If possible, add an element of fun
• Add data to help remove emotion
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Key Elements of a Decision Matrix
• Clear problem statement
• Definition of options being considered
• Factors that make options more desirable
• Weights on Factors
• Unambiguous scoring criteria for each factor
• Calculated Decision based on scores and weights
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Problem Statement
• Clear and complete
• Team consensus
• Form of a question is helpful
• Revisit if questions arise during the process
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Options
• Short list (<10) of possible answers to the question being asked in the problem statement
• Options need to be clear and not overlap
• Only include viable options that do not violate constraints
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Factors
• Factors that make options more desirable
• Generally 5 – 10 options
• Not related to each other
- For example, don’t want 5 out of 10 to be related to cost
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Weights
• Recommend 3, 7, 10 scale
• Not everything can be a 10, need some at every level
• Need team agreement on definitions
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Scoring Criteria
• Unambiguous scoring criteria for each factor
- Critical to team agreement on scores
- Use of specific scoring criteria facilitates team consensus
1 1
3
5 5
7
10 10
1 1
3 3
5 5
7 7
10 10
1 1
3 3
5 5
7 7
10 10
1
3
5
7
10
Scoring Criteria for
Neighborhood
High crime-rate area, no amenities
Above average crime rates, few
Average crime rates, some amenities
Below average crime rates, amenities
Very low crime rate, many amenities
Scoring Criteria for
Monthly Rent
>$2000
$1600-$2000
$1200-1600
$800-1200
<$800
Scoring Criteria for
Parking
Street parking only.
--
Complex has an open parking lot for
--
Personal parking space or garage.
Scoring Criteria for
Laundry
No on-site laundry available.
--
Shared laundry facility in the complex.
--
Washer and dryer in the unit.
Scoring Criteria for
# of Bedrooms
No Bedrooms. Studio apartment.
--
1 Bedroom.
--
2+ Bedrooms.
Average commute :30 mins or less
Scoring Criteria for
Space/Sq. Feet
<500 sq. feet.
500 - 600 sq. feet.
600 - 800 sq. feet.
800 - 1000 sq. feet.
>1000 sq. feet.
Scoring Criteria for
Distance to Work
Average commute: >60mins
--
Average commute: between 30 and
--
3
7
10
Generic Scoring Criteria
Scoring Criteria
Below Average
Good
Exceptional
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Scores
• Don’t average scores across the team
- Need to discuss enough to understand alternate viewpoints and share information across the team
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Calculated Decision
• Calculated Decision based on scores and weights
• Sum of products
-Weighting x Score
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Goldilocks and Her Team Choose Porridge
Temperature 10 3 3 10
Lumpiness 10 10 3 7
Whole grains 7 3 7 3
Viscosity 7 7 3 10
23 16 30
Which bowl of porridge should we eat?
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Decision Making
FactorsWeighting
Weighted Decision:
Options Baby Bear
Scores
200 130
Papa Bear Mama Bear
RAW SCORE:
3 3
7 7
10 10
3 3
7 7
10 10
no whole grains
mix of whole grains and processed grains
100% whole grains
Scoring Criteria -
Viscosity
very thim, like milk
very thick, almost solid
neither thin nor thick
Scoring Criteria -
Lumpiness
many large lumps
a few small lumps
no lumps
Scoring Criteria -
Whole Grains
Scoring Criteria -
Temperature150 <= temp <= 180
temp < 150 degrees
temp > 180 degrees
3
7
10
Moderate Importance
High Importance
Critical
Weighing Criteria
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Wrap Up
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Thank You!
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© Honeywell International